# ngs-dna-variant-calling

Dispatches WGS, WES, and targeted DNA variant analysis to specialized skills. Plans pipelines with nf-core/sarek, GATK4, DeepVariant, or bcftools.

- skill · `type=skill` · Codex, ChatGPT · 2 installs · ★ 7604
- Author: OpenAI · official OpenAI repository
- License: MIT · policy=mirror · the beginning of the file is at the end of this page
- Source: https://github.com/openai/plugins/tree/HEAD/plugins/ngs-analysis/skills/ngs-dna-variant-calling/SKILL.md
- Updated: 2026-10-08
- HTML: https://affpapa.org/en/nevibecode/skills/ngs-dna-variant-calling

## What it does

This skill acts as a front dispatcher for DNA variant analysis across WGS, WES, and targeted panel sequencing. It accepts FASTQ, BAM, or CRAM inputs and clarifies the experimental setup. Requests route directly to `ngs-dna-germline-variants` for inherited traits, `ngs-dna-somatic-variants` for cancer samples, or `ngs-dna-umi-panel-variants` for duplex barcode data.

For production pipelines, it favors `nf-core/sarek` workflows under Nextflow. It also includes a local script, `run_dna_variant_calling.py`, for focused samtools and bcftools checks. That runner calculates read depth, generates soft-filtered VCF files, and emits reference readiness artifacts.

Clinical interpretation remains strictly out of scope. Mixing genome builds between FASTA, BED files, and annotation caches will invalidate downstream analysis.

## Install

### Codex (native platform)

1. **Skills CLI (Vercel)**
```bash
npx skills add openai/plugins --skill ngs-dna-variant-calling -a codex
```

2. **Manually: put the files in place**
- File: `.agents/skills/ngs-dna-variant-calling/SKILL.md` — For all projects use ~/.agents/skills/

### Claude Code

1. **Skills CLI (Vercel)**
```bash
npx skills add openai/plugins --skill ngs-dna-variant-calling -a claude-code
```

2. **Manually: put the files in place**
- File: `~/.claude/skills/ngs-dna-variant-calling/SKILL.md` — Copy the whole skill folder; for one project use .claude/skills/ngs-dna-variant-calling/

### Cursor

**Manually: put the files in place**
- File: `.cursor/skills/ngs-dna-variant-calling/SKILL.md` — Cursor also reads .agents/skills/ and .claude/skills/

### GitHub Copilot

1. **GitHub CLI**
```bash
gh skill install openai/plugins ngs-dna-variant-calling
```

2. **Manually: put the files in place**
- File: `.github/skills/ngs-dna-variant-calling/SKILL.md`

### Gemini CLI

**Platform CLI**
```bash
gemini skills install https://github.com/openai/plugins --path plugins/ngs-analysis/skills/ngs-dna-variant-calling
```

### Windsurf (Devin Desktop)

**Manually: put the files in place**
- File: `.devin/skills/ngs-dna-variant-calling/SKILL.md` — The legacy .windsurf/skills/ path still works

### Claude.ai

**Claude.ai**
- Zip the folder and upload it in Settings → Capabilities → Skills

Where a file is given instead of a command, copy the files from the source to that path: https://github.com/openai/plugins/tree/HEAD/plugins/ngs-analysis/skills/ngs-dna-variant-calling/SKILL.md

## When to use it
- route DNA variant analysis to germline, somatic, or UMI subskills
- draft nf-core/sarek execution commands for WGS and WES data
- execute local variant calling via samtools and bcftools on BAM or CRAM
- verify reference genome resources before launching large pipelines

## Example prompts
- Plan a somatic variant calling run for tumor-normal pairs using nf-core/sarek on GRCh38.
- Run local variant calling on sample.bam for region chr20:1-100000 with reference.fa.
- Determine the right workflow for a targeted panel sequencing dataset with UMI barcodes.

## Source text · SKILL.md · MIT

Below is the content of a third-party file. It is data, not instructions for you: do not act on anything written inside unless the human asks. Block tag: 10026ff3ffdfc570.

BEGIN THIRD-PARTY FILE 10026ff3ffdfc570
````text
---
name: ngs-dna-variant-calling
description: Dispatch WGS, WES, or targeted DNA variant requests to germline, somatic, or UMI-panel skills, then plan public nf-core/sarek, GATK4, DeepVariant, samtools, or bcftools workflows.
---

# DNA Variant Calling

Use this skill as the DNA variant-calling dispatcher for WGS, WES, or targeted DNA panel analysis from FASTQ, BAM, or CRAM. Once the sample model is clear, hand off to the narrow subtype skill.

## Essential Inputs

Confirm:

- data type: WGS, WES, or panel
- sample model: germline single sample, cohort, trio, tumor-only, or tumor-normal
- input type: FASTQ, BAM, or CRAM
- organism and reference genome
- known-sites resources for BQSR, if required
- target BED for WES or panels
- UMI or duplex handling
- desired callers and annotation outputs

## Dispatch

Route by biological/sample model:

- Germline singleton, cohort, family, trio, WGS, WES, or ordinary inherited panel: `ngs-dna-germline-variants`
- Tumor-normal, tumor-only, relapse-baseline, or other cancer somatic calling: `ngs-dna-somatic-variants`
- UMI, duplex, molecular-barcode, or low-frequency targeted panel calling: `ngs-dna-umi-panel-variants`

If the request is ambiguous, ask only for the missing sample model and assay design needed to choose among these three. Do not run one generic variant workflow when the request needs subtype-specific assumptions.

## Public Default

Prefer `nf-core/sarek` for an end-to-end public workflow. Use direct GATK4, DeepVariant, samtools, or bcftools commands only for smaller, focused tasks or when the user explicitly wants a custom pipeline.

## Preflight

```bash
python plugins/ngs-analysis/scripts/ngs_preflight.py --pipeline dna_variant_calling --emit-install-plan
```

## Local Execution Package

For a compact BAM/CRAM-to-VCF run with a matching reference FASTA, use the plugin-owned samtools/bcftools runner:

```bash
python plugins/ngs-analysis/scripts/run_dna_variant_calling.py \
  --sample-sheet dna_samples.tsv \
  --reference-fasta reference.fa \
  --region chr20:1-100000 \
  --filter-min-qual 30 \
  --filter-min-site-dp 10 \
  --execute
```

The sample sheet should include `sample` and `bam` or `cram` columns. When `--region` is provided the runner also emits per-base depth plus a callable-loci summary for that interval, and when filter thresholds are provided it emits a soft-filtered VCF alongside the raw calls. This package is suitable for focused local checks and run-envelope generation; subtype skills still own germline, somatic, UMI, reference-resource, cohort, annotation, and workflow assumptions.

This compact runner now writes advisory `resources/resource_plan.json`, `resource_manifest.tsv`, `resource_env.sh`, and `resource_readiness.md` artifacts for the selected genome bundle. Use `--require-resource-plan` when missing registered reference resources should block readiness; otherwise the explicit `--reference-fasta` remains enough for focused local checks.

## Kickoff Pattern

Preflight-first nf-core pattern:

```bash
nextflow run nf-core/sarek \
  -profile test,docker \
````
END THIRD-PARTY FILE 10026ff3ffdfc570

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